Our proposed research is aimed at developing catalytic molecules and methods that greatly improve the recovery of biomolecular information from formalin-fixed tissue specimens. Formalin (formaldehyde) treatment of tissue is universally used in preparation of hundreds of millions of biopsy and surgery specimens worldwide. Unfortunately, the formaldehyde forms many adducts and crosslinks with the biomolecules in the specimens, strongly inhibiting the ability to obtain sequences and quantification of RNAs and DNAs from such specimens, Standard heating-based methods of RNA/DNA extraction remove only a fraction of adducts, and they are harsh, degrading the nucleic acids in the process. In our preliminary work using model nucleotides in vitro, we have shown that bifunctional organic arylamine catalysts can be highly effective in removing hemiaminal formaldehyde adducts of RNA/DNA bases under mild conditions of pH and temperature. Recovery of undamaged nucleotides and RNAs is markedly enhanced as compared with standard methods, and the catalysts can be effective even at room temperature. This work takes an innovative, mechanistic chemistry-based approach to reversal of formaldehyde adducts. The goal of this 6-month collaborative research plan is to establish convincing proof-of-principle that our organocatalysts can be used to recover greater amounts of bimolecular signals from formalin-adducted RNA and DNA than literature-standard and commercial buffers and protocols do. The work will be carried out at cell Data Sciences Inc. and at Stanford School of Medicine. While our early work has been performed primarily with simple nucleotide models, here we plan to develop and optimize catalysts with full-length RNAs and DNAs, and secondly, to extend our protocols and catalysts to extracting, repairing and analyzing clinically relevant RNAs and DNAs in cell- and tissue-based FFPE specimens. We expect that this work will constitute a major breakthrough in retrieval of molecular data from formalin-fixed tissue, solving a widely recognized and decades-long problem. These catalysts will enable higher-yield retrieval of longer, less damaged RNAs and DNAs from tissue specimens, allowing access to sequence where it was not possible, and enhancing quantitative signals where they were previously weak or unquantifiable. Our approach will give stronger signals from PCR analysis and more accurate and complete sequencing data with fewer reads. It will also enable more robust signals from in situ hybridization. Finally, the catalysts may also remove crosslinks and adducts from proteins; this could yield stronger signals by immunohistochemistry and could enable more effective proteomics analyses from stored tissue.